Short-range order (SRO) is an important structural characteristic in multiprincipal element alloys (MPEAs) that plays a crucial role in their superior mechanical and physical properties. The development of SRO is usually tangled with structural evolution associated with diffusion-induced atomic transport, making it challenging to accurately determine the diffusion coefficients in MPEAs based on conventional modeling techniques. In this study, we combine machine learning with kinetic Monte Carlo to compute the self-diffusion coefficients in NiCoCr and NiFeCr MPEAs with distinct SRO tendencies under long-time structural evolution. Our results show that the long-term diffusion process governed by thermodynamic and kinetic factors can promote SRO formation due to chemically biased exchange between vacancy and specific components in the alloy. We further demonstrate that accurate diffusion coefficients in MPEAs can only be obtained through long-term simulations allowing for sufficient structural evolution. This study underlines the shortcomings of the presently widely employed techniques to study diffusion in MPEAs and highlights the intricate coupling between SRO and diffusion.
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